4.7 Article

Further results on exponential stability of neural networks with time-varying delay

Journal

APPLIED MATHEMATICS AND COMPUTATION
Volume 256, Issue -, Pages 175-182

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2015.01.004

Keywords

Neural networks; Time-varying delay; Exponential stability; Lyapunov-Krasovskii functional

Funding

  1. National Natural Science Foundation of China [61125301, 61210011]
  2. Fundamental Research Funds for the Central Universities of Central South University [2014zzts205]

Ask authors/readers for more resources

This paper investigates the problem of the exponential stability for a class of neural networks with time-varying delay. A triple integral term and a term considering the delay information in a new way are introduced to the Lyapunov-Krasovskii functional (LKF). The obtained criterion show advantages over the existing ones since not only a novel LKF is constructed but also several techniques such as Wirtinger-based inequality and convex combination technique are used to estimate the upper bound of the derivative of the LKF. Finally, a numerical example is provided to verify the effectiveness and benefit of the proposed criterion. (C) 2015 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available